Overview

Dataset statistics

Number of variables26
Number of observations300000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory59.5 MiB
Average record size in memory208.0 B

Variable types

NUM16
CAT10

Warnings

id has unique values Unique

Reproduction

Analysis started2021-02-08 22:16:30.340495
Analysis finished2021-02-08 22:18:10.237024
Duration1 minute and 39.9 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

id
Real number (ℝ≥0)

UNIQUE

Distinct300000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean250018.5769
Minimum1
Maximum499999
Zeros0
Zeros (%)0.0%
Memory size2.3 MiB
2021-02-09T09:18:10.433822image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile24987.95
Q1124772.5
median250002.5
Q3375226.5
95-th percentile475032.1
Maximum499999
Range499998
Interquartile range (IQR)250454

Descriptive statistics

Standard deviation144450.15
Coefficient of variation (CV)0.5777576681
Kurtosis-1.202249332
Mean250018.5769
Median Absolute Deviation (MAD)125228
Skewness0.0001529463078
Sum7.500557308e+10
Variance2.086584584e+10
MonotocityStrictly increasing
2021-02-09T09:18:10.570859image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
20491< 0.1%
 
1589511< 0.1%
 
1774041< 0.1%
 
1671631< 0.1%
 
1651141< 0.1%
 
1712571< 0.1%
 
1896861< 0.1%
 
1958291< 0.1%
 
1937801< 0.1%
 
1814901< 0.1%
 
Other values (299990)299990> 99.9%
 
ValueCountFrequency (%) 
11< 0.1%
 
21< 0.1%
 
31< 0.1%
 
41< 0.1%
 
61< 0.1%
 
ValueCountFrequency (%) 
4999991< 0.1%
 
4999981< 0.1%
 
4999971< 0.1%
 
4999961< 0.1%
 
4999931< 0.1%
 

cat0
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
A
281471 
B
 
18529
ValueCountFrequency (%) 
A28147193.8%
 
B185296.2%
 
2021-02-09T09:18:10.688889image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-02-09T09:18:10.750905image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:10.829923image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

cat1
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
A
162678 
B
137322 
ValueCountFrequency (%) 
A16267854.2%
 
B13732245.8%
 
2021-02-09T09:18:10.935946image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-02-09T09:18:11.003962image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:11.080766image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

cat2
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
A
276551 
B
 
23449
ValueCountFrequency (%) 
A27655192.2%
 
B234497.8%
 
2021-02-09T09:18:11.174789image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-02-09T09:18:11.233803image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:11.299818image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

cat3
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
C
183752 
A
104464 
D
 
11174
B
 
610
ValueCountFrequency (%) 
C18375261.3%
 
A10446434.8%
 
D111743.7%
 
B6100.2%
 
2021-02-09T09:18:11.401841image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-02-09T09:18:11.475154image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:11.561855image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

cat4
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
B
297373 
A
 
1241
C
 
767
D
 
619
ValueCountFrequency (%) 
B29737399.1%
 
A12410.4%
 
C7670.3%
 
D6190.2%
 
2021-02-09T09:18:11.667879image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-02-09T09:18:11.740895image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:11.819916image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

cat5
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
B
149208 
D
135151 
C
 
11763
A
 
3878
ValueCountFrequency (%) 
B14920849.7%
 
D13515145.1%
 
C117633.9%
 
A38781.3%
 
2021-02-09T09:18:11.932944image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-02-09T09:18:12.006960image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:12.082978image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

cat6
Categorical

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
A
292643 
B
 
6344
C
 
809
D
 
147
I
 
24
Other values (3)
 
33
ValueCountFrequency (%) 
A29264397.5%
 
B63442.1%
 
C8090.3%
 
D147< 0.1%
 
I24< 0.1%
 
E19< 0.1%
 
H11< 0.1%
 
G3< 0.1%
 
2021-02-09T09:18:12.184157image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-02-09T09:18:12.257174image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:12.352196image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

cat7
Categorical

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
E
267631 
D
 
24356
B
 
5750
G
 
1961
F
 
279
Other values (3)
 
23
ValueCountFrequency (%) 
E26763189.2%
 
D243568.1%
 
B57501.9%
 
G19610.7%
 
F2790.1%
 
A14< 0.1%
 
C6< 0.1%
 
I3< 0.1%
 
2021-02-09T09:18:12.451218image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-02-09T09:18:12.524234image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:12.640260image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

cat8
Categorical

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
C
121054 
E
94616 
G
42195 
A
37878 
D
 
3694
Other values (2)
 
563
ValueCountFrequency (%) 
C12105440.4%
 
E9461631.5%
 
G4219514.1%
 
A3787812.6%
 
D36941.2%
 
F5490.2%
 
B14< 0.1%
 
2021-02-09T09:18:12.741283image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-02-09T09:18:12.820301image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:12.910326image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

cat9
Categorical

Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
F
107281 
I
50064 
L
42200 
H
24759 
K
20955 
Other values (10)
54741 
ValueCountFrequency (%) 
F10728135.8%
 
I5006416.7%
 
L4220014.1%
 
H247598.3%
 
K209557.0%
 
A134084.5%
 
G104093.5%
 
M98383.3%
 
J69812.3%
 
O61732.1%
 
Other values (5)79322.6%
 
2021-02-09T09:18:13.015349image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-02-09T09:18:13.113372image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

cont0
Real number (ℝ)

Distinct299830
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.524633789
Minimum-0.09350536055
Maximum1.052665996
Zeros0
Zeros (%)0.0%
Memory size2.3 MiB
2021-02-09T09:18:13.337422image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-0.09350536055
5-th percentile0.2514193718
Q10.3704508256
median0.4922083191
Q30.6547925468
95-th percentile0.9326039757
Maximum1.052665996
Range1.146171357
Interquartile range (IQR)0.2843417212

Descriptive statistics

Standard deviation0.2048746106
Coefficient of variation (CV)0.3905097516
Kurtosis-0.2241451429
Mean0.524633789
Median Absolute Deviation (MAD)0.1397477691
Skewness0.5098842266
Sum157390.1367
Variance0.04197360607
MonotocityNot monotonic
2021-02-09T09:18:13.496458image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.45607140252< 0.1%
 
0.68019878092< 0.1%
 
0.49303806062< 0.1%
 
0.46830743752< 0.1%
 
0.34619656672< 0.1%
 
0.33729726562< 0.1%
 
0.34895778612< 0.1%
 
0.49889031732< 0.1%
 
0.36095640622< 0.1%
 
0.5089189922< 0.1%
 
Other values (299820)299980> 99.9%
 
ValueCountFrequency (%) 
-0.093505360551< 0.1%
 
-0.084291164771< 0.1%
 
-0.081515288751< 0.1%
 
-0.077237202561< 0.1%
 
-0.075904733411< 0.1%
 
ValueCountFrequency (%) 
1.0526659961< 0.1%
 
1.0479629121< 0.1%
 
1.0447002981< 0.1%
 
1.0444690891< 0.1%
 
1.043916121< 0.1%
 

cont1
Real number (ℝ)

Distinct299642
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5066489299
Minimum-0.05510510604
Maximum0.8517463757
Zeros0
Zeros (%)0.0%
Memory size2.3 MiB
2021-02-09T09:18:13.795525image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-0.05510510604
5-th percentile0.04928001596
Q10.3523071228
median0.6151562832
Q30.6881497715
95-th percentile0.7756661163
Maximum0.8517463757
Range0.9068514817
Interquartile range (IQR)0.3358426487

Descriptive statistics

Standard deviation0.2352694791
Coefficient of variation (CV)0.4643639121
Kurtosis-0.6912706609
Mean0.5066489299
Median Absolute Deviation (MAD)0.1322055851
Skewness-0.7264677191
Sum151994.679
Variance0.05535172781
MonotocityNot monotonic
2021-02-09T09:18:13.923563image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.76098761372< 0.1%
 
0.55162125382< 0.1%
 
0.75332569832< 0.1%
 
0.67084533722< 0.1%
 
0.63743631242< 0.1%
 
0.65087644112< 0.1%
 
0.62044385342< 0.1%
 
0.73113816732< 0.1%
 
0.63893265842< 0.1%
 
0.043425319132< 0.1%
 
Other values (299632)299980> 99.9%
 
ValueCountFrequency (%) 
-0.055105106041< 0.1%
 
-0.049315084741< 0.1%
 
-0.048832829981< 0.1%
 
-0.047787595451< 0.1%
 
-0.046762152471< 0.1%
 
ValueCountFrequency (%) 
0.85174637571< 0.1%
 
0.84757612161< 0.1%
 
0.84736496541< 0.1%
 
0.84725838921< 0.1%
 
0.84574086251< 0.1%
 

cont2
Real number (ℝ)

Distinct299707
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4441147267
Minimum-0.06027372205
Maximum1.017689219
Zeros0
Zeros (%)0.0%
Memory size2.3 MiB
2021-02-09T09:18:14.210627image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-0.06027372205
5-th percentile0.1279779537
Q10.3141211439
median0.4572706105
Q30.5548352803
95-th percentile0.7856643395
Maximum1.017689219
Range1.077962941
Interquartile range (IQR)0.2407141364

Descriptive statistics

Standard deviation0.2000885238
Coefficient of variation (CV)0.4505334135
Kurtosis-0.1517279878
Mean0.4441147267
Median Absolute Deviation (MAD)0.1299177548
Skewness0.1710232658
Sum133234.418
Variance0.04003541735
MonotocityNot monotonic
2021-02-09T09:18:14.380666image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.45858417132< 0.1%
 
0.16781120632< 0.1%
 
0.40730227582< 0.1%
 
0.64426257442< 0.1%
 
0.3915720952< 0.1%
 
0.45053761072< 0.1%
 
0.35228143862< 0.1%
 
0.66085487292< 0.1%
 
0.4343960142< 0.1%
 
0.39332251022< 0.1%
 
Other values (299697)299980> 99.9%
 
ValueCountFrequency (%) 
-0.060273722051< 0.1%
 
-0.057261831141< 0.1%
 
-0.055846781141< 0.1%
 
-0.054476253631< 0.1%
 
-0.054087015751< 0.1%
 
ValueCountFrequency (%) 
1.0176892191< 0.1%
 
1.0140342281< 0.1%
 
1.0131207561< 0.1%
 
1.0127653141< 0.1%
 
1.0046108621< 0.1%
 

cont3
Real number (ℝ≥0)

Distinct299796
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4462141003
Minimum0.134759848
Maximum1.006468677
Zeros0
Zeros (%)0.0%
Memory size2.3 MiB
2021-02-09T09:18:14.643724image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.134759848
5-th percentile0.1697756861
Q10.2145721353
median0.3778233694
Q30.7197584307
95-th percentile0.8231545671
Maximum1.006468677
Range0.8717088288
Interquartile range (IQR)0.5051862955

Descriptive statistics

Standard deviation0.238669041
Coefficient of variation (CV)0.5348756142
Kurtosis-1.362968261
Mean0.4462141003
Median Absolute Deviation (MAD)0.1839353469
Skewness0.4015277675
Sum133864.2301
Variance0.05696291111
MonotocityNot monotonic
2021-02-09T09:18:14.775754image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.38522057922< 0.1%
 
0.74498624792< 0.1%
 
0.21491842112< 0.1%
 
0.19474281842< 0.1%
 
0.34776422272< 0.1%
 
0.3579324372< 0.1%
 
0.16000228982< 0.1%
 
0.16603210262< 0.1%
 
0.7475540622< 0.1%
 
0.34988131742< 0.1%
 
Other values (299786)299980> 99.9%
 
ValueCountFrequency (%) 
0.1347598481< 0.1%
 
0.13566043941< 0.1%
 
0.13620608031< 0.1%
 
0.13638814831< 0.1%
 
0.13644024151< 0.1%
 
ValueCountFrequency (%) 
1.0064686771< 0.1%
 
1.0039402911< 0.1%
 
0.99697318041< 0.1%
 
0.99109771231< 0.1%
 
0.98870896931< 0.1%
 

cont4
Real number (ℝ≥0)

Distinct299736
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.455471435
Minimum0.1892162896
Maximum0.9940500684
Zeros0
Zeros (%)0.0%
Memory size2.3 MiB
2021-02-09T09:18:15.386892image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.1892162896
5-th percentile0.2768757143
Q10.2798526181
median0.4113511369
Q30.621808131
95-th percentile0.8272805699
Maximum0.9940500684
Range0.8048337788
Interquartile range (IQR)0.3419555129

Descriptive statistics

Standard deviation0.2006950827
Coefficient of variation (CV)0.4406315463
Kurtosis-0.8981667078
Mean0.455471435
Median Absolute Deviation (MAD)0.1319898
Skewness0.7436693388
Sum136641.4305
Variance0.04027851622
MonotocityNot monotonic
2021-02-09T09:18:15.518922image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.27929195343< 0.1%
 
0.71964300262< 0.1%
 
0.25876917242< 0.1%
 
0.27741505062< 0.1%
 
0.27834402732< 0.1%
 
0.2783507522< 0.1%
 
0.28025940142< 0.1%
 
0.2792044592< 0.1%
 
0.27992626212< 0.1%
 
0.27766134972< 0.1%
 
Other values (299726)299979> 99.9%
 
ValueCountFrequency (%) 
0.18921628961< 0.1%
 
0.19152128261< 0.1%
 
0.19273859491< 0.1%
 
0.19289586911< 0.1%
 
0.19446623911< 0.1%
 
ValueCountFrequency (%) 
0.99405006841< 0.1%
 
0.98378582391< 0.1%
 
0.97467628921< 0.1%
 
0.97340290521< 0.1%
 
0.97113894961< 0.1%
 

cont5
Real number (ℝ)

Distinct299857
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5083365866
Minimum-0.08724666205
Maximum1.044433461
Zeros0
Zeros (%)0.0%
Memory size2.3 MiB
2021-02-09T09:18:15.778981image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-0.08724666205
5-th percentile0.2114987688
Q10.3387473087
median0.4413842656
Q30.7095145248
95-th percentile0.9226693048
Maximum1.044433461
Range1.131680123
Interquartile range (IQR)0.3707672161

Descriptive statistics

Standard deviation0.2316121906
Coefficient of variation (CV)0.455627623
Kurtosis-0.9605123321
Mean0.5083365866
Median Absolute Deviation (MAD)0.1697970386
Skewness0.5111504075
Sum152500.976
Variance0.05364420686
MonotocityNot monotonic
2021-02-09T09:18:15.912010image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.38607248922< 0.1%
 
0.24089080872< 0.1%
 
0.26634967012< 0.1%
 
0.37780933692< 0.1%
 
0.79915628772< 0.1%
 
0.4438145652< 0.1%
 
0.74873635782< 0.1%
 
0.27282343872< 0.1%
 
0.86640420482< 0.1%
 
0.33977598622< 0.1%
 
Other values (299847)299980> 99.9%
 
ValueCountFrequency (%) 
-0.087246662051< 0.1%
 
-0.018928345781< 0.1%
 
0.017326783681< 0.1%
 
0.027891739311< 0.1%
 
0.030552985541< 0.1%
 
ValueCountFrequency (%) 
1.0444334611< 0.1%
 
1.0410972351< 0.1%
 
1.0401650771< 0.1%
 
1.0399241911< 0.1%
 
1.039795451< 0.1%
 

cont6
Real number (ℝ≥0)

Distinct299875
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4783452172
Minimum0.04395333548
Maximum1.093311508
Zeros0
Zeros (%)0.0%
Memory size2.3 MiB
2021-02-09T09:18:16.175070image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.04395333548
5-th percentile0.2481665982
Q10.3398959616
median0.410089752
Q30.6042464047
95-th percentile0.8689058501
Maximum1.093311508
Range1.049358172
Interquartile range (IQR)0.2643504431

Descriptive statistics

Standard deviation0.1924322851
Coefficient of variation (CV)0.4022874656
Kurtosis-0.1490648539
Mean0.4783452172
Median Absolute Deviation (MAD)0.09975577419
Skewness0.8710045443
Sum143503.5652
Variance0.03703018436
MonotocityNot monotonic
2021-02-09T09:18:16.304099image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.60989125412< 0.1%
 
0.23508688142< 0.1%
 
0.39648713762< 0.1%
 
0.24667464012< 0.1%
 
0.27306135872< 0.1%
 
0.39858725772< 0.1%
 
0.39320072622< 0.1%
 
0.25378430242< 0.1%
 
0.93184011042< 0.1%
 
0.36507644992< 0.1%
 
Other values (299865)299980> 99.9%
 
ValueCountFrequency (%) 
0.043953335481< 0.1%
 
0.050541539021< 0.1%
 
0.051914134391< 0.1%
 
0.052081558241< 0.1%
 
0.052330086751< 0.1%
 
ValueCountFrequency (%) 
1.0933115081< 0.1%
 
1.0867691561< 0.1%
 
1.0856608261< 0.1%
 
1.0849253611< 0.1%
 
1.0847504911< 0.1%
 

cont7
Real number (ℝ≥0)

Distinct299832
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.45590421
Minimum0.2087026958
Maximum1.036540503
Zeros0
Zeros (%)0.0%
Memory size2.3 MiB
2021-02-09T09:18:16.557156image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.2087026958
5-th percentile0.2397147848
Q10.2780409482
median0.3607356108
Q30.6393880398
95-th percentile0.8533803757
Maximum1.036540503
Range0.8278378069
Interquartile range (IQR)0.3613470916

Descriptive statistics

Standard deviation0.2044927142
Coefficient of variation (CV)0.4485431581
Kurtosis-0.7468133166
Mean0.45590421
Median Absolute Deviation (MAD)0.1122627755
Skewness0.7051679981
Sum136771.263
Variance0.04181727015
MonotocityNot monotonic
2021-02-09T09:18:16.680183image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.28511575472< 0.1%
 
0.34396326182< 0.1%
 
0.47341629232< 0.1%
 
0.65136465862< 0.1%
 
0.30069367962< 0.1%
 
0.32493873662< 0.1%
 
0.76577988962< 0.1%
 
0.23219705142< 0.1%
 
0.76333945892< 0.1%
 
0.66186412412< 0.1%
 
Other values (299822)299980> 99.9%
 
ValueCountFrequency (%) 
0.20870269581< 0.1%
 
0.20946652091< 0.1%
 
0.21015806421< 0.1%
 
0.21050907331< 0.1%
 
0.21055377861< 0.1%
 
ValueCountFrequency (%) 
1.0365405031< 0.1%
 
1.0357240381< 0.1%
 
1.0354705691< 0.1%
 
1.031458981< 0.1%
 
1.0296858061< 0.1%
 

cont8
Real number (ℝ≥0)

Distinct299765
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4593209938
Minimum0.004041388119
Maximum1.014155557
Zeros0
Zeros (%)0.0%
Memory size2.3 MiB
2021-02-09T09:18:16.930240image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.004041388119
5-th percentile0.1405207448
Q10.3086545446
median0.4258013333
Q30.5415252359
95-th percentile0.9077543621
Maximum1.014155557
Range1.010114169
Interquartile range (IQR)0.2328706913

Descriptive statistics

Standard deviation0.220641617
Coefficient of variation (CV)0.4803647558
Kurtosis-0.09412954961
Mean0.4593209938
Median Absolute Deviation (MAD)0.1169121001
Skewness0.725130309
Sum137796.2982
Variance0.04868272316
MonotocityNot monotonic
2021-02-09T09:18:17.061269image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.30411547562< 0.1%
 
0.36573065132< 0.1%
 
0.45906155452< 0.1%
 
0.50232626682< 0.1%
 
0.87107577322< 0.1%
 
0.87611310152< 0.1%
 
0.40408380672< 0.1%
 
0.60347797812< 0.1%
 
0.41626616442< 0.1%
 
0.87093182742< 0.1%
 
Other values (299755)299980> 99.9%
 
ValueCountFrequency (%) 
0.0040413881191< 0.1%
 
0.0044901927411< 0.1%
 
0.0095371063341< 0.1%
 
0.0096169912111< 0.1%
 
0.01022423931< 0.1%
 
ValueCountFrequency (%) 
1.0141555571< 0.1%
 
1.0134019271< 0.1%
 
1.0126617641< 0.1%
 
1.0118703341< 0.1%
 
1.0112922811< 0.1%
 

cont9
Real number (ℝ≥0)

Distinct299863
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5268991427
Minimum0.07303994469
Maximum0.9720914516
Zeros0
Zeros (%)0.0%
Memory size2.3 MiB
2021-02-09T09:18:17.321328image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.07303994469
5-th percentile0.232363823
Q10.3619570588
median0.4888671825
Q30.7527645954
95-th percentile0.8337855587
Maximum0.9720914516
Range0.899051507
Interquartile range (IQR)0.3908075366

Descriptive statistics

Standard deviation0.204025052
Coefficient of variation (CV)0.3872184171
Kurtosis-1.211933365
Mean0.5268991427
Median Absolute Deviation (MAD)0.1550879577
Skewness0.2232278554
Sum158069.7428
Variance0.04162622184
MonotocityNot monotonic
2021-02-09T09:18:17.460359image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.78305584732< 0.1%
 
0.81563563592< 0.1%
 
0.63179128342< 0.1%
 
0.82070006442< 0.1%
 
0.81769084782< 0.1%
 
0.81268613532< 0.1%
 
0.8075008152< 0.1%
 
0.1964858552< 0.1%
 
0.81733600672< 0.1%
 
0.34614893012< 0.1%
 
Other values (299853)299980> 99.9%
 
ValueCountFrequency (%) 
0.073039944691< 0.1%
 
0.080506578721< 0.1%
 
0.080912625861< 0.1%
 
0.082675981971< 0.1%
 
0.083407009181< 0.1%
 
ValueCountFrequency (%) 
0.97209145161< 0.1%
 
0.96900387231< 0.1%
 
0.9655122221< 0.1%
 
0.96346161391< 0.1%
 
0.96295780891< 0.1%
 

cont10
Real number (ℝ≥0)

Distinct299894
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5049429014
Minimum0.05964379697
Maximum1.029773341
Zeros0
Zeros (%)0.0%
Memory size2.3 MiB
2021-02-09T09:18:17.725920image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.05964379697
5-th percentile0.1945640674
Q10.338897848
median0.519854825
Q30.6728090213
95-th percentile0.8382278076
Maximum1.029773341
Range0.9701295439
Interquartile range (IQR)0.3339111733

Descriptive statistics

Standard deviation0.201548871
Coefficient of variation (CV)0.3991518059
Kurtosis-0.9044132014
Mean0.5049429014
Median Absolute Deviation (MAD)0.1685714556
Skewness0.08465076136
Sum151482.8704
Variance0.04062194739
MonotocityNot monotonic
2021-02-09T09:18:17.865952image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.48625610412< 0.1%
 
0.27644180872< 0.1%
 
0.57569277332< 0.1%
 
0.65901479342< 0.1%
 
0.29322419672< 0.1%
 
0.74085128212< 0.1%
 
0.61810246882< 0.1%
 
0.72723384142< 0.1%
 
0.74362062912< 0.1%
 
0.3374675582< 0.1%
 
Other values (299884)299980> 99.9%
 
ValueCountFrequency (%) 
0.059643796971< 0.1%
 
0.063149828471< 0.1%
 
0.066553820251< 0.1%
 
0.069784221461< 0.1%
 
0.069983732981< 0.1%
 
ValueCountFrequency (%) 
1.0297733411< 0.1%
 
1.0286273921< 0.1%
 
1.0273787011< 0.1%
 
1.0251058111< 0.1%
 
1.0250256361< 0.1%
 

cont11
Real number (ℝ≥0)

Distinct299877
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5299381007
Minimum0.06416121457
Maximum1.038048933
Zeros0
Zeros (%)0.0%
Memory size2.3 MiB
2021-02-09T09:18:18.131049image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.06416121457
5-th percentile0.191424597
Q10.3166618274
median0.5588266091
Q30.7203810423
95-th percentile0.8677535134
Maximum1.038048933
Range0.9738877186
Interquartile range (IQR)0.4037192148

Descriptive statistics

Standard deviation0.2308599637
Coefficient of variation (CV)0.4356357156
Kurtosis-1.383586373
Mean0.5299381007
Median Absolute Deviation (MAD)0.2033826778
Skewness-0.03074609761
Sum158981.4302
Variance0.05329632286
MonotocityNot monotonic
2021-02-09T09:18:18.265120image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.74540323752< 0.1%
 
0.71243070572< 0.1%
 
0.69971798052< 0.1%
 
0.7089487352< 0.1%
 
0.67994140242< 0.1%
 
0.72542313752< 0.1%
 
0.42938405022< 0.1%
 
0.65786440582< 0.1%
 
0.27575540152< 0.1%
 
0.27198237342< 0.1%
 
Other values (299867)299980> 99.9%
 
ValueCountFrequency (%) 
0.064161214571< 0.1%
 
0.065623279321< 0.1%
 
0.068165433331< 0.1%
 
0.069159094771< 0.1%
 
0.0707656791< 0.1%
 
ValueCountFrequency (%) 
1.0380489331< 0.1%
 
1.0364727051< 0.1%
 
1.0347235631< 0.1%
 
1.0337628131< 0.1%
 
1.032730211< 0.1%
 

cont12
Real number (ℝ)

Distinct299824
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5245492482
Minimum-0.005599995244
Maximum0.9613704167
Zeros0
Zeros (%)0.0%
Memory size2.3 MiB
2021-02-09T09:18:18.518177image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-0.005599995244
5-th percentile0.2767894312
Q10.3321430521
median0.4073648664
Q30.7324313196
95-th percentile0.880974641
Maximum0.9613704167
Range0.9669704119
Interquartile range (IQR)0.4002882675

Descriptive statistics

Standard deviation0.2208917893
Coefficient of variation (CV)0.4211078178
Kurtosis-1.461532898
Mean0.5245492482
Median Absolute Deviation (MAD)0.1241142907
Skewness0.3728983307
Sum157364.7745
Variance0.04879318256
MonotocityNot monotonic
2021-02-09T09:18:18.658208image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.337965172< 0.1%
 
0.30573344282< 0.1%
 
0.32806739772< 0.1%
 
0.35851068142< 0.1%
 
0.35030797692< 0.1%
 
0.33738376362< 0.1%
 
0.26917038882< 0.1%
 
0.34416629322< 0.1%
 
0.32035467682< 0.1%
 
0.35334267012< 0.1%
 
Other values (299814)299980> 99.9%
 
ValueCountFrequency (%) 
-0.0055999952441< 0.1%
 
0.01380501691< 0.1%
 
0.015351099321< 0.1%
 
0.018977722491< 0.1%
 
0.028222951571< 0.1%
 
ValueCountFrequency (%) 
0.96137041671< 0.1%
 
0.96066129081< 0.1%
 
0.95871550081< 0.1%
 
0.9585336591< 0.1%
 
0.95807157931< 0.1%
 

cont13
Real number (ℝ≥0)

Distinct299866
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.503349028
Minimum0.1581209416
Maximum0.8735786266
Zeros0
Zeros (%)0.0%
Memory size2.3 MiB
2021-02-09T09:18:18.939052image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0.1581209416
5-th percentile0.207126659
Q10.2912885661
median0.433908679
Q30.7308702762
95-th percentile0.8168110085
Maximum0.8735786266
Range0.7154576849
Interquartile range (IQR)0.4395817102

Descriptive statistics

Standard deviation0.2252176585
Coefficient of variation (CV)0.4474383498
Kurtosis-1.634448892
Mean0.503349028
Median Absolute Deviation (MAD)0.2096072261
Skewness0.1307868945
Sum151004.7084
Variance0.05072299368
MonotocityNot monotonic
2021-02-09T09:18:19.100089image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.62730814922< 0.1%
 
0.2880950532< 0.1%
 
0.38848773832< 0.1%
 
0.26868972082< 0.1%
 
0.269943532< 0.1%
 
0.26824421382< 0.1%
 
0.39562111132< 0.1%
 
0.41101999372< 0.1%
 
0.79112546522< 0.1%
 
0.68128154632< 0.1%
 
Other values (299856)299980> 99.9%
 
ValueCountFrequency (%) 
0.15812094161< 0.1%
 
0.1582653981< 0.1%
 
0.15863292321< 0.1%
 
0.1598247921< 0.1%
 
0.16018193791< 0.1%
 
ValueCountFrequency (%) 
0.87357862661< 0.1%
 
0.86641600481< 0.1%
 
0.86562727211< 0.1%
 
0.86477026661< 0.1%
 
0.86403033121< 0.1%
 

target
Real number (ℝ≥0)

Distinct299648
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.456260484
Minimum0
Maximum10.30920751
Zeros1
Zeros (%)< 0.1%
Memory size2.3 MiB
2021-02-09T09:18:19.416160image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.986960362
Q16.798340504
median7.496503224
Q38.161166382
95-th percentile8.769955955
Maximum10.30920751
Range10.30920751
Interquartile range (IQR)1.362825879

Descriptive statistics

Standard deviation0.8872947048
Coefficient of variation (CV)0.1189999607
Kurtosis-0.4364989081
Mean7.456260484
Median Absolute Deviation (MAD)0.6804074946
Skewness-0.2012646961
Sum2236878.145
Variance0.7872918932
MonotocityNot monotonic
2021-02-09T09:18:19.586198image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
6.1082855113< 0.1%
 
6.9327137922< 0.1%
 
5.6255733282< 0.1%
 
5.7335413882< 0.1%
 
7.6100311972< 0.1%
 
8.0501841072< 0.1%
 
6.6900324242< 0.1%
 
8.0381912252< 0.1%
 
5.8923552852< 0.1%
 
7.6409241212< 0.1%
 
Other values (299638)299979> 99.9%
 
ValueCountFrequency (%) 
01< 0.1%
 
2.3910294381< 0.1%
 
2.6488980661< 0.1%
 
2.8575567111< 0.1%
 
3.3436457061< 0.1%
 
ValueCountFrequency (%) 
10.309207511< 0.1%
 
10.290964831< 0.1%
 
10.282248561< 0.1%
 
10.279137591< 0.1%
 
10.257308781< 0.1%
 

Interactions

2021-02-09T09:17:08.255092image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:08.497147image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:08.728199image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:08.961253image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:09.201310image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:09.437977image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:09.681807image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:09.915860image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:10.144912image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:10.386966image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:10.639023image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:10.891080image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:11.106129image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:11.322178image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:11.540226image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:11.761275image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:11.966322image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:12.172368image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:12.378415image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:12.583461image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:12.798509image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:13.007557image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:13.221605image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:13.458661image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:13.686712image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:13.913586image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:14.147642image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:14.466714image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:14.684776image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:14.911199image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:15.142883image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:17:15.372935image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2021-02-09T09:18:01.095563image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:01.318613image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:01.541091image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:01.770952image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:02.004848image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:02.234592image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:02.468645image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:02.696696image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:02.914745image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:03.125792image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:03.329839image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:03.538885image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:03.780940image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:03.994137image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:04.202184image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:04.415232image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:04.628281image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:04.851330image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:05.085383image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:05.294430image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:05.520509image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:05.743675image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:05.967725image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Correlations

2021-02-09T09:18:19.747234image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-02-09T09:18:19.985288image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-02-09T09:18:20.192842image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-02-09T09:18:20.399890image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2021-02-09T09:18:20.608956image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-02-09T09:18:07.052908image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-02-09T09:18:08.376061image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Sample

First rows

idcat0cat1cat2cat3cat4cat5cat6cat7cat8cat9cont0cont1cont2cont3cont4cont5cont6cont7cont8cont9cont10cont11cont12cont13target
01ABAABDAECI0.9231910.6849680.1244540.2178860.2814210.8811220.4216500.7414130.8957990.8024610.7244170.7019150.8776180.7199036.994023
12BAAABBAEAF0.4376270.0142130.3574380.8461270.2823540.4400110.3462300.2784950.5934130.5460560.6132520.7412890.3266790.8084648.071256
23AAACBDABCN0.7322090.7601220.4546440.8129900.2937560.9141550.3696020.8325640.8656200.8252510.2641040.6955610.8691330.8283525.760456
34AAACBDAEGK0.7051420.7716780.1537350.7328930.7697850.9341380.5789300.4073130.8680990.7944020.4942690.6981250.8097990.6147667.806457
46ABAABBAECF0.4860630.6393490.4962120.3541860.2791050.3826000.7059400.3251930.4409670.4621460.7244470.6830730.3434570.2977436.868974
57AAACBBAEEB0.3197230.7415070.6489460.4348440.2806910.2455600.2173620.6062980.3452820.3512350.3719400.2227820.2792270.7736007.060652
68ABACBDAEGF0.8672270.0674490.1991450.8409790.2780680.9312660.6331570.7841850.9127040.8011540.5997860.9016560.8374740.6744776.165491
79BABCBBAECL0.3482040.6198190.5508460.1824650.7842940.3631300.3493240.2527340.4741700.4340620.7295850.5754550.6951250.2243108.100110
810ABBABDAEEF0.9209950.4869930.2446550.1965580.2789930.9496770.5329240.7223100.9244950.8126240.5941730.8842720.8167020.7775388.180236
911ABACBDAEEG0.8531320.3531980.1898640.2492990.2812670.8257220.6260830.3108010.9440500.4916950.5623090.5550270.6155980.4841176.589764

Last rows

idcat0cat1cat2cat3cat4cat5cat6cat7cat8cat9cont0cont1cont2cont3cont4cont5cont6cont7cont8cont9cont10cont11cont12cont13target
299990499980AAACBDADGF0.8994010.7629420.1143740.7003060.2794280.8701740.7764370.7170390.9279520.8463310.9021400.8981020.8733160.7825366.199239
299991499985AAADBBAECK0.4420360.4181430.3249730.2768040.5209990.3385260.8385080.3723580.4046630.7222280.4255980.8508280.3655470.6975587.892157
299992499988ABACBBAEEL0.3921580.0583070.4988620.4169670.4241670.2640940.3220220.2546360.3103040.3145880.2448610.2576670.3310810.7956668.199213
299993499989AAAABDADAF0.5243880.2989470.5042070.2812600.5567540.7830500.6917950.6943920.4948580.5223010.7882280.8515420.8912900.7337868.365215
299994499992AAAABDAECF0.4741550.7449860.4913790.1763380.5845470.7309740.5786030.3296310.5033060.5553140.7136840.4283040.6473980.8015956.783325
299995499993ABACBBAEEL0.2607160.7124380.1616610.4427940.7684470.2695780.2586550.3635980.3006190.3405160.2357110.3834770.2152270.7936308.343538
299996499996ABACBBAEEL0.1733020.1215910.5925140.1937110.7759510.1972110.2570240.5743040.2270350.3225830.2860940.3248740.3069330.2309027.851861
299997499997ABACBBAECM0.3428560.6178690.4629910.4180980.2974060.4494820.3861720.4762170.1359470.5027300.2357880.3166710.2502860.3490417.600558
299998499998ABBCBBADEF0.5994030.6860540.6608600.1871990.7586420.3631300.3241320.2290170.2208880.5153040.3893910.2452340.3038950.4811388.272095
299999499999AABABDAECK0.4754510.0376590.7537720.3981290.6960470.7347120.4041450.4977190.4979740.7825850.7512510.6084120.7128680.4524006.025685